AI Data Engineer

Microsoft is seeking a highly skilled Data Analyst and Business Intelligence professional to join a dynamic team focused on transforming complex operational and infrastructure data into trusted, actionable insights. In this fully remote role, you will analyze large datasets related to power, cooling, environmental systems, and critical infrastructure while designing scalable reporting solutions to drive operational excellence.

Responsibilities:

• Partner with engineering, operations, program management, and leadership teams to define data requirements and develop analytics solutions that drive informed decision-making
• Analyze large and complex datasets to identify trends, anomalies, gaps, risks, and opportunities for operational improvement
• Perform data quality assessments, validation, and verification to ensure accuracy, completeness, consistency, and integrity across multiple sources and systems
• Design, implement, automate, and maintain scalable data collection, transformation, and validation processes that reduce manual effort and improve reliability
• Develop and maintain dashboards, scorecards, KPI reporting, and self-service analytics solutions that provide visibility into operational performance, telemetry health, and business outcomes
• Create data validation frameworks, monitoring processes, and quality controls to proactively detect and resolve data issues
• Collaborate with technical teams to improve data models, metadata management, reporting structures, and overall data governance practices
• Translate complex technical findings into clear, actionable insights and recommendations tailored for both technical and executive audiences
• Drive continuous improvement through automation, standardization, and implementation of scalable reporting and analytics solutions
• Support root cause analysis and investigative efforts by leveraging data to identify underlying drivers of performance issues and operational risks
• Document processes, methodologies, reporting requirements, and data quality standards to ensure consistency and scalability

Requirements:

• 4+ years of experience conducting data quality verification to ensure accuracy, completeness, and consistency across critical infrastructure data sources
• 4+ years of experience performing data analysis to identify trends, anomalies, gaps, and performance opportunities
• 3+ years of experience developing intuitive dashboards and reports providing clear visibility into metrics, operational health, and program outcomes
• Experience in business intelligence, reporting, data quality management, or related analytical disciplines
• Bachelor's degree in Computer Science, Computer Engineering, or a related technical field required
• 5–7 years of applicable professional experience required
• Strong data quality validation, verification, and monitoring expertise with the ability to ensure accuracy and integrity across multiple data sources
• Proficiency developing dashboards and visualizations using business intelligence tools such as Power BI, Tableau, or similar platforms
• Experience analyzing telemetry, operational, IoT, industrial controls, or critical infrastructure data including power and cooling systems
• Ability to automate manual processes using scripting, workflow automation, or data integration technologies
• Strong troubleshooting, problem-solving, analytical thinking, and investigative skills with a focus on identifying root causes
• Experience developing executive-level dashboards and KPI scorecards that communicate complex findings to diverse audiences
• Solid written and verbal communication skills with the ability to present insights clearly to both technical and non-technical stakeholders
• Demonstrated success delivering scalable solutions that improve efficiency, data accuracy, and operational visibility
• Background working with data center or equivalent critical infrastructure environments including power distribution and environmental systems strongly preferred
• Experience with data center or critical infrastructure health and performance data is highly desirable
• Familiarity with automated data validation and exception management processes